Load Enable Banking data to DuckDB

Enable Banking is an open banking aggregation API providing account information and payment initiation services across European financial institutions. Everything needed to build a working Enable Banking → DuckDB pipeline is on this page: the API's base URL, authentication, endpoints, pagination and incremental field — plus a prompt that hands the whole job to your coding agent.

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Build your Enable Banking to DuckDB pipeline

Paste this prompt into Claude, Codex, or Cursor. The agent does the rest.

PromptCopy prompt
Run uvx dlthub-init@latest to build a pipeline from Enable Banking to DuckDB and run it on dltHub

That scaffolds a dltHub workspace and installs the dltHub AI harness — the project rules, the secrets-management skill, and the dlt MCP server your agent needs to work safely. From there it reads the Enable Banking API, proposes the endpoints to load, then writes, runs and validates the pipeline while you review rather than type. Credentials are inspected through MCP tools, so your agent never reads secrets.toml itself. How the LLM-native workflow works →

Prefer to write it yourself? Every fact the agent uses is below.

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Enable Banking API at a glance

These values come from the Enable Banking API reference — the authoritative source if anything here looks out of date.

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How do I authenticate with the Enable Banking API?

Authentication requires an application-issued JWT signed with RS256 using a private RSA key. The JWT must be passed in the 'Authorization' header using the 'Bearer' scheme (e.g., 'Authorization: Bearer ').

1. Get your credentials

To obtain credentials for the Enable Banking REST API, follow these steps: 1. Sign in to the Enable Banking Control Panel at https://enablebanking.com/sign-in/. 2. Navigate to the 'API applications' page via the top menu. 3. Select your environment (Sandbox or Production). 4. Click to add a new application and fill out the required details (application name, whitelisted redirect URLs). 5. You can choose to allow the browser to generate a private RSA key (which will be downloaded to your machine) or provide your own public key. 6. Submit the form to register your application and receive a unique Application ID. The downloaded .pem file serves as your private key for generating authentication tokens.

2. Add them to .dlt/secrets.toml

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[sources.enable_banking_source]
application_id = "your_application_uuid_here"
private_key_path = "/path/to/your_application_id.pem"

dlt reads this file automatically at runtime. With the harness, the setup-secrets skill prompts you for the values and never handles the raw credential in chat. For production, see setting up credentials with dlt.

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What Enable Banking data can I load into DuckDB?

These are the Enable Banking endpoints dlt can load into DuckDB:

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How do I load only new Enable Banking records?

Enable Banking exposes continuation_key on accounts/{account_id}/transactions, so dlt can request only the records that changed since the last run. Set it as the cursor_path and dlt tracks the high-water mark for you between runs.

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{"name": "account_transactions", "endpoint": {
    "path": "accounts/{account_id}/transactions",
    "data_selector": "transactions",
    "incremental": {"cursor_path": "continuation_key", "initial_value": "2024-01-01T00:00:00Z"},
}}

On the first run dlt loads everything from initial_value; on every run after that it requests only what changed and appends with write_disposition="merge" if you set a primary key. See incremental loading.

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What does the generated Enable Banking pipeline look like?

A standard dlt REST API pipeline — the same code you would write by hand, loading auth and sessions from the Enable Banking API into DuckDB:

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import dlt
from dlt.sources.rest_api import RESTAPIConfig, rest_api_resources

@dlt.source
def enable_banking_source(app_id=dlt.secrets.value):
    config: RESTAPIConfig = {
        "client": {
            "base_url": "https://api.enablebanking.com",
            "auth": {"type": "bearer", "token": app_id},
        },
        "resources": [
            {"name": "account_transactions", "endpoint": {"path": "accounts/{account_id}/transactions", "data_selector": "transactions"}},
            {"name": "aspsps", "endpoint": {"path": "aspsps", "data_selector": "aspsps"}}
        ],
    }
    yield from rest_api_resources(config)


def load_enable_banking_to_duckdb() -> None:
    pipeline = dlt.pipeline(
        pipeline_name="enable_banking_pipeline",
        destination="duckdb",
        dataset_name="enable_banking_data",
    )
    load_info = pipeline.run(enable_banking_source())
    print(load_info)


if __name__ == "__main__":
    load_enable_banking_to_duckdb()

Run it with python enable_banking_pipeline.py. The agent iterates on this until it loads cleanly — you review and approve, rather than write it from scratch.

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How do I query Enable Banking data in DuckDB?

dlt creates one table per resource. Query the loaded data with Python or SQL — or ask your agent to, through the MCP server's execute_sql_query tool.

Python (pandas DataFrame):

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import dlt

data = dlt.pipeline("enable_banking_pipeline").dataset()
df = data.account_transactions.df()
print(df.head())

SQL:

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SELECT * FROM enable_banking_data.account_transactions LIMIT 10;

See querying your data with dataset and exploring it in marimo notebooks.

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How do I deploy the Enable Banking to DuckDB pipeline in production?

The pipeline runs locally, which is ideal for prototyping and one-off analysis. When you need it on a schedule, monitored on every load, and shared with your team, deploy the same dlt code on the dltHub platform — no infrastructure to maintain. The prompt above already ends with "run it on dltHub", so your agent can take it there directly.

• Deploy & schedule — run the pipeline as a managed job with automatic retries.
• Monitor — observable job queues, alerting, and load metrics for every run.
• Transform — promote raw Enable Banking loads into governed, documented models.
• Visualize & share — explore data in notebooks and publish live dashboards instead of static screenshots.

Book a demo →

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What other destinations can I load Enable Banking data to?

dlt loads into any of these — only the destination argument changes:

Set dlt.pipeline(destination="snowflake") and add credentials in .dlt/secrets.toml. On the dltHub platform the same pipeline runs against a managed Iceberg lakehouse. See the full destinations list.

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Next steps

• Ready for production? Book a demo of the dltHub platform →
• dlt LLM-native workflow docs
• REST API source reference
• Join the dlt community on Slack